Complex systems, such as vehicles, aircraft, spacecraft and other systems, typically include many subsystems for controlling and managing the vehicle and performing missions. Throughout the specification, it should be understood that a reference to a vehicle encompasses a variety of complex systems. It is desirable to identify adverse events or failures and degradation that may be occurring in one or more of these subsystems, particularly during real-time operation of the ground or air vehicle. Integrated Vehicle Health Management systems may be used to monitor, and diagnose various characteristics (failure modes, equipment usage, degradation events) of the vehicle. Model-based systems using models, rules, decisions, and cases (i.e., expert systems) about system behavior have been developed to create a functional model of a system that receives and evaluates inputs from sensors and other data sources within the vehicle and compares observation with the model blueprint to deliver diagnostics. However, prior art models are integrated only at a subsystem, e.g. component, level instead of encompassing an entire vehicle. In addition, a large amount of time, resources, and budget are required to develop and update the model in response to hardware and software upgrades over the life-cycle of the vehicle.
A rules based approach to engineering diagnostics solutions may use built-in test (BIT) data. BIT Engineering (considered to be fixed rules based approach) is not very effective for complex systems and is the main reason for high false alarm (FA) rates observed in various vehicle modes of operation. The engineering effort involved in producing good rules is very costly and unaffordable in software and hardware upgrades over decades; therefore, the costs of maintaining these systems is immense—nearly 72% of the life-cycle cost goes in operations and support. This increases the sustainment cost required to maintain vehicles over their lifecycle. In addition, equipment BIT information may be supplied by different vendors and generally does not follow a consistent standard. Environment conditions play an important role in equipment usage and mission planning. For instance, high dragging winds may cause equipment to be used in excessive operational modes (increasing vibrations, temperatures, wear and tear in rotating mechanisms, etc.) causing early degradation and decrease in remaining useful life (RUL) of the equipment. Large gravitational forces can cause diminished structural integrity, loss of future capability, and downtime for repair and replacement. BIT information is not effective in taking such varying environmental conditions, mission profiles, and structural integrity into consideration.
The sensor data associated with some sensors, e.g. pressure, temperature, volume, flow, etc., is normally produced at a relatively low data rates, i.e. low frequency, e.g. 1 Hz-50 Hz. Because of the relatively low data rate of information provided by such sensors, the processing of this information, even where information must be processed in parallel from several such sensors, can be easily handled by modern microprocessors. However, there exists a need to accommodate the processing and analysis of information from other sensors that have a high frequency data output rate, e.g. in the kilohertz to low megahertz range. Current vehicle systems do not adequately handle high frequency sensors, especially in payloads, structures, and non-critical mechanical components.